library(ggthemes)
library(tmap)
library(countrycode)
pal = tableau_color_pal(
palette = "Tableau 10")(10)
data("World")
World = World%>%
filter(continent!="Antarctica")
World$wb=countrycode(sourcevar = World$iso_a3,
origin = "iso3c",
destination = "region")
## Warning in countrycode_convert(sourcevar = sourcevar, origin = origin, destination = dest, : Some values were not matched unambiguously: ATF, ESH, SOL, UNK, XTX
World = World%>%
filter(!is.na(wb))
tmap_mode("plot")
## tmap mode set to plotting
tm_shape(World) +
tm_polygons("wb",palette=pal)

load("worldbankindicators.RData")
tmap_mode("view")
## tmap mode set to interactive viewing
currentdata = worldbank_data%>%
filter(!is.na(Values))%>%
filter(year == 2020)%>%
mutate(iso_a3 =
countrycode(sourcevar = .$iso2c,
origin = "iso2c",
destination = "iso3c"))%>%
filter(!is.na(iso_a3))
## Warning in countrycode_convert(sourcevar = sourcevar, origin = origin, destination = dest, : Some values were not matched unambiguously: 1A, 1W, 4E, 7E, 8S, B8, EU, F1, JG, OE, S1, S2, S3, S4, T2, T3, T4, T5, T6, T7, V1, V2, V3, V4, XC, XD, XE, XF, XG, XH, XI, XJ, XK, XL, XM, XN, XO, XP, XQ, XT, XU, Z4, Z7, ZF, ZG, ZH, ZI, ZJ, ZQ, ZT
vars = World%>%left_join(currentdata)
## Joining, by = "iso_a3"
tm_shape(vars) +
tm_polygons("Values")+
tm_facets(by = "Indicator",free.scales=TRUE)
## Variable(s) "Values" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
#source("inflationdata.R")
load("inflationdata.RData")
data = data%>%
mutate(date=as.POSIXct(date))%>%
mutate(region = countrycode(sourcevar = data$region,
origin = "iso3n",
destination = "region")
)%>%
drop_na()%>%
group_by(region,`Series Name`,date)%>%
summarise(value=median(value,na.rm=T))%>%
drop_na()%>%
mutate(series = `Series Name`)%>%
nest(data = -c(region,series))%>%
mutate(
test = map(data, ~ loess(.$value~as.numeric(.$date), span = .5)), # S3 list-col
tidied = map(test, augment,se.fit=T
)
)%>%
unnest(c(tidied,data))%>%
select(-test)%>%
data.frame()%>%
mutate(smooth = `.fitted`)
## `summarise()` has grouped output by 'region', 'Series Name'. You can override
## using the `.groups` argument.
alt$data_transformers$disable_max_rows()
## DataTransformerRegistry.enable('default')
selection = alt$selection_multi(fields=list("region"), bind='legend')
chart <-
alt$Chart(data)$
encode(
x = "date:T",
y = "smooth:Q",
color="region:N",
tooltip='date:T',
opacity=alt$condition(selection, alt$value(1), alt$value(0.2))
)$
mark_line()$
facet('series',columns=2)$
interactive()$
add_selection(
selection
)
chart